TargetScore-package {TargetScore} | R Documentation |
Infer the posterior distributions of microRNA targets by probabilistically modeling the likelihood microRNA-overexpression fold-changes and sequence-based scores. Variational Bayesian Gaussian mixture model (VB-GMM) is applied to log fold-changes and sequence scores to obtain the posteriors of latent variable being the miRNA targets. The final targetScore is computed as the sigmoid-transformed fold-change weighted by the averaged posteriors of target components over all of the features.
Package: | TargetScore |
Type: | Package |
Version: | 1.1.5 |
Date: | 2013-10-15 |
License: | GPL-2 |
The front-end main function targetScore
should be used to obtain the probablistic score of miRNA target. The workhourse function is vbgmm
, which implementates multivariate variational Bayesian Gaussian mixture model.
Yue Li <yueli@cs.toronto.edu>
Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., Schelter, J. M., Castle, J., Bartel, D. P., Linsley, P. S., and Johnson, J. M. (2005). Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature, 433(7027), 769-773.
Bartel, D. P. (2009). MicroRNAs: Target Recognition and Regulatory Functions. Cell, 136(2), 215-233.
Bishop, C. M. (2006). Pattern recognition and machine learning. Springer, Information Science and Statistics. NY, USA. (p474-486)
library(TargetScore) ls("package:TargetScore")